Computers and computer software to perform image acquisition, image processing, and image rendering techniques have increasingly become common in today's digital world. For example, an increasing number of motion pictures, video, and games utilize image processing techniques to artificially render images. Computer-generated images are increasingly replacing conventionally obtained images, particularly in situations where special effects are warranted.
So-called “motion tracking” or “motion capture” began as an analysis tool in biomechanics research, and expanded into education, training, sports and recently computer animation for cinema and video games as the technology has matured.
In the current art, a performer wears markers near each joint to identify the motion by the positions or angles between the markers. Acoustic, inertial, LED, magnetic or reflective markers, or combinations of any of these, are tracked, optimally at least two times the rate of the desired motion, to submillimeter positions. The motion capture computer software records the positions, angles, velocities, accelerations and impulses, providing an accurate digital representation of the motion.
In entertainment applications, the application of motion tracking can reduce the costs of animation which otherwise requires the animator to draw each frame, or with more sophisticated software, key frames which are interpolated by the software. Motion capture saves time and creates more natural movements than manual animation. In biomechanics, sports and training, real time data can provide the necessary information to diagnose problems or suggest ways to improve performance, requiring motion capture technology to capture motions up to 140 miles per hour for a golf swing, for example.
Certain disadvantages also continue to pose problems for motion tracking technologies. For example, current algorithms and techniques often break down when applied to recreate human characteristics in computer-generated characters, resulting in “cartoon-like” reproductions. Moreover, current methods and techniques often result in poorer resolution and clarity than is desired, particularly when applied to humanistic features such as facial expressions and the like.
Thus, a need exists for a method of capturing, processing, and rendering images which provides increased resolution and clarity. In addition, a need exists for a method which implements various corrective “fixes” to promote greater resolution, clarity, and overall quality in reproduction.